PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Stefan Bracke Co-author(s): Alicia Puls; apuls@uni-wuppertal.de
| COVID-19 pandemic: Analyzing spreading behavior of different infection waves within the first two years in Germany by the use of reliability methods |
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| Since December 2019, the world is confronted with the COVID-19 pandemic, caused by the Coronavirus SARS-CoV-2. The COVID-19 pandemic with its incredible speed of spread shows the vulnerability of a globalized and networked world. The first two years of the pandemic were characterized by several infections waves, marked by different spreading behaviors, described by length, peak and speed. The infection waves caused a heavy burden on health systems and severe restrictions on public life within a lot of countries, like educational system shutdown, travel restrictions, limitations regarding public life or a comprehensive lockdown. The goal of the presented research study is the analysis of the development of the four dominant infection waves in Germany within the first two years of COVID-19 pandemic time period (February 2020 – February 2022). The analyses are focusing on infection occurrence and spreading behavior, in detail on attributes like length, peak and speed of each wave. Furthermore various impacts of lockdown strategies (hard, soft) or health protection measures, vaccination status and virus mutations are considered. The analyze of the infection waves is based on a transfer and application of methods – especially the Weibull distribution model and statistical hypothesis tests – used in reliability engineering for analyzing the upcoming failure development within product fleets in the field. This study continues previous research; cf. Puls and Bracke (2021), Bracke et al. (2021) and Puls and Bracke. The spreading behavior of a COVID-19 infection wave can be described by Weibull distribution model in a sound way, related to a short time interval. The interpretation of the Weibull model parameters allows the assessment of the COVID-19 infection wave characteristics and generates additional information to classical infection analyzing models like the SIR model (Kermack and Kendrick 1927). Furthermore, statistical hypothesis tests are used to analyze the observed characteristics of the infection waves with regard to their significance. Observations like change points, trends, peaks and further systematically developments within the infection situation and the resulting potential risk can be substantiated. Finally, the characteristics of the COVID-19 infection waves are analyzed in the context of other common infectious diseases in Germany like Influenza or Norovirus. Differences in the spreading behavior of COVID-19 in comparison to these well-known infectious diseases are underlined for different pandemic phases. REFERENCES A. Puls and S. Bracke (2021). Reliability Methods for analyzing COVID-10 pandemic spreading behavior, lockdown impact and infectiousness. In: Proceedings of the 31th European Safety and Reliability Conference (Eds.: Bruno Castanier, Marko Cepin, David Bigaud and Christophe Berenguer). Research Publishing Services, Singapore. S. Bracke, A. Puls and M. Inoue (2021). COVID-19 pandemic: Analyzing of restrictions, medical care and prevention measures in Germany and Japan. In: Proceedings of the 31th European Safety and Reliability Conference (Eds.: Bruno Castanier, Marko Cepin, David Bigaud and Christophe Berenguer), Research Publishing Services, Singapore. A. Puls and S. Bracke (2021). COVID-19 pandemic risk analytics: Data mining with reliability engineering methods for analyzing spreading behavior and comparison with infectious diseases. In: van Gulijk C., Zaitseva E. (eds) Reliability Engineering and Computational Intelligence. Studies in Computational Intelligence, vol 976. Springer. Kermack, W.O., A.G. McKendrick (1927), A Contribution to the Mathematical Theory of Epidemics. Proc. Roy. Soc. A, Vol. 115, pp. 700-721. |
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Author and Presentation Info
Lead Author Name: Stefan Bracke (bracke@uni-wuppertal.de)
Bio: 1991 – 1995 Studies of Mechanical Engineering; University of Bochum 1997 – 1999 Doctor´s Thesis: „Quality strategies regarding to the reuse of components of technical products within the product remanufacturing (product recycling)” 1996 – 1999 University of Bochum, Chair of Manufacturing System Planning, Prof. Dr.-Ing. H. Schnauber, Section: Quality Planning and Control 1996 – 2000 Consultancy INNOSYS GmbH & Co. KG; Quality Management, Bochum, Germany 2000 – 2006 Dr. Ing. h.c. F. Porsche AG, Department of Quality Management, Stuttgart, Germany 2007 – 2010 Cologne University of Applied Sciences, Cologne, Germany Faculty of Vehicle Systems and Production, Institute of Production, Professor; Department of Quality Management and Production Metrology Since 10.2010 University of Wuppertal, Germany, Faculty of Safety Engineering Professorship: Chair of Reliability Engineering and Risk Analytics Since 04.2016 Guest Professorship at Meiji University, Kawasaki, Tokio, Japan
Country: Germany
Company: University of Wuppertal
Job Title: Professor
Bio: 1991 – 1995 Studies of Mechanical Engineering; University of Bochum 1997 – 1999 Doctor´s Thesis: „Quality strategies regarding to the reuse of components of technical products within the product remanufacturing (product recycling)” 1996 – 1999 University of Bochum, Chair of Manufacturing System Planning, Prof. Dr.-Ing. H. Schnauber, Section: Quality Planning and Control 1996 – 2000 Consultancy INNOSYS GmbH & Co. KG; Quality Management, Bochum, Germany 2000 – 2006 Dr. Ing. h.c. F. Porsche AG, Department of Quality Management, Stuttgart, Germany 2007 – 2010 Cologne University of Applied Sciences, Cologne, Germany Faculty of Vehicle Systems and Production, Institute of Production, Professor; Department of Quality Management and Production Metrology Since 10.2010 University of Wuppertal, Germany, Faculty of Safety Engineering Professorship: Chair of Reliability Engineering and Risk Analytics Since 04.2016 Guest Professorship at Meiji University, Kawasaki, Tokio, Japan
Country: Germany
Company: University of Wuppertal
Job Title: Professor